Frequently Asked Questions about using the ALSWH data (last updated: July, 2020)

Xenia Dolja-Gore, Peta Forder, David Fitzgerald, Carl Holder, Richard Hockey, Jeeva Kanesarajah, Michael Waller

Data Management

Getting started with the ALSWH data

·         Important information you many need to know as a data user can be found on our website at .  On this webpage you will find information about the surveys, getting started, responses for each of the items asked in the surveys (Data Books) and information on how variables have been derived (Data Dictionary and Data Dictionary Supplement) just click on the links to learn more.  Importantly please read the following prior to getting started:

o   Notes for Collaborators has useful information for first time users of the ALSWH data  ( ).  This webpage gives an introduction to each cohort, the study representativeness and attrition and notes relating to naming conventions for datasets and variables and missing data.

o   Variable names, labels and formats for each cohort and survey can be accessed by clicking on the ‘Survey Variables’ option or directly by using this web address 

  • You can weight for area of residence at Survey 1 (y1wtarea, m1wtarea, o1wtarea) in all crosstabs, frequencies and analyses to adjust for the initial deliberate oversampling in rural and remote areas. This is not required when running models that include area of residence.

·         Check the data map, the data dictionary and Data Dictionary Supplement for further information about survey items and derived variables. They are available at

·         Data must be downloaded and stored onto a secured environment as soon as it is received.  Analysis undertaken must only be in accordance with the approved EOI.  Changes to the nature of the analysis must be approved by the ALSWH Data Access Committee.

·         All publications must include the appropriate acknowledgments. (

.     How to read in a SAS dataset with formats already attached

Linking Administrative dataset to ALSWH

·         If your project includes linkage of datasets, use the ‘IDproj’ ’ key variable for joining the datasets.

·         You should have the list of women opting out of the data linkage project(s).  These women will not be in the linked data and should be considered. 

·         Make sure when merging your survey and administrative datasets you ensure only consented women have been added to the combined outcome file.  Note:  in some cases all participants are required for the analysis but this should be confirmed by your ALSWH liaison.

·         Useful notes for data users linking the PBS and MBS data may be found in Tech Report 38 – December 2015 page 118  ( and Tech Report 39 page 71 ( ).

·         Medicare variable formats may be found on the ALSWH website at

·         Dummy PBS and MBS data are available for testing and development here: . Information regarding these data is available here: .

Missing data issues

·         Some participants completed a short survey instead of the full survey, accounting for some missing data. This occurred in Survey 2 for the three original cohorts and Survey 3 for the 1921-26 and 1946-51 cohorts.  The variable ‘**survey’,  has the value 2 for a short survey and one otherwise..

Filling in Missing data

·         Handy references at

·         References for representativeness and attrition may be found at

·         Comments on survey missing data:

Statistics Analysis

Useful programming code

·         Reliable programming code to join multiple files may be found for SAS and Stata programmers at the following webpages:

o   Useful SAS code clearly explained by Wieczkowski, Michael J. Alternatives to Merging SAS Data Sets. But Be Careful.  IMS HEALTH, Plymouth Meeting, PA ( ). Also see .

o   Stata code:

·         Included on our website is the stripping program to change variable names – making wide to long transformation easier:

·         Information on enduring conditions is in Tech Report #29 here

(Datasets with these variables may be requested by following the link ))

Derived Variables

·         Questions related to the Food Frequency Questionnaire may be found at

·         Be careful that you do not inappropriately analyse single items from a scale. For example, the 36 items in the SF-36 should not be considered as separate items, other than the first self-rated health item. The Data Dictionary Supplement has details about which scales have been included in the surveys.  (

·         Commonly used data variable cut-points may be found in the Data Dictionary Supplement or at for the following:

o   Physical activity in Report 21 page 104

o   Mental health cut-points for possible psychosocial distress in Report 16 pages 48 and 66

o   Notes regarding methods of standardising life events may be found in Report 31 page 106

Resources to help you get started

·         This could be a link to the SAS webpage, UCLA or STATA FAQ page





Free SAS tutorials

Useful paper to reference

How to cite this web page:

For example: Frequently Asked Questions.  Australian Longitudinal Study on Women’s Health.  from http:// (accessed November 10, 2016). 

 image of woman's face with data

Data Release

Survey 7 1973-78 (Young) cohort – data now available

Data are now available from the seventh survey of ALSWH’s 1973-78 cohort. The survey ran from April 2015 to September 2016 and 7,186 women provided valid responses. The participants were aged between 37 and 42 years old at the time of the survey. The women have now been surveyed seven times since they were recruited in 1996. Variables included in each survey include:

  • Smoking
  • BMI
  • Alcohol
  • Quality of life
  • Exercise
  • Mental health
  • Health usage
  • Sexual health
  • Reproductive health
  • Demographics

What’s New in Survey 7

For the first time, women in this cohort were asked about:

  • Use of stairs on a usual day
  • Pain in various parts of the body
  • Adverse Childhood Experiences (ACE)
  • More childbirth information, e.g., birth weight and sex of each child

The ACE is a collaboration between the Center for Disease Control and Prevention and Kaiser Permanente's Health Appraisal Clinic in San Diego. ACE have been linked to risky health behaviours, chronic health conditions, disadvantage and early death.

Accessing the data

The data book containing macro-level data from this survey is available from the ALSWH website

More detailed survey data including qualitative responses may be accessed through the study’s Expression of Interest process



Information for Data Users

Data Books

View and download the data books.

Data Dictionary

View and download the ALSWH Data Dictionary .

Survey Variables

View and download lists of variables for each survey

Data Dictionary Supplement

Data Dictionary Supplement information.

Data Map

View and download the ALSWH Data Map .

Notes for Collaborators using ALSWH data

Notes compiled for collaborators who use ALSWH data.

Notes for Collaborators using ALSWH Core data

Notes for Collaborators - who use ADA-Accessed (Core) data.

Food Frequency Information / Dietary Questionnaire for Epidemiology Studies

Food Frequency information.

Policy statement on data relating to the health of Aboriginal and Torres Strait Islander women

The ALSWH statement on data relating to the health of Aboriginal and Torres Strait Islander women .

Disseminating and Promoting your Results

Jump to a topic below:


All publications (including those using data from external datasets linked with survey data) must include the following acknowledgement:

The research on which this (paper, book, monograph, abstract or report) is based was conducted as part of the Australian Longitudinal Study on Women's Health by the University of Queensland and the University of Newcastle. We are grateful to the Australian Government Department of Health for funding and to the women who provided the survey data.

Press Releases

Press releases must be approved by the ALSWH Liaison person and must include the correct ALSWH acknowledgement, as follows:

The research on which this press release is based was conducted as part of the Australian Longitudinal Study on Women's Health by the University of Queensland and the University of Newcastle. We are grateful to the Australian Government Department of Health for funding and to the women who provided the survey data.

If linked data were used it must be acknowledged that the linkages were done by the Australian Longitudinal Study on Women's Health (also known as Women's Health Australia).

Publishing Linked Data

Please refer to the Requirements for Publishing Linked Data section on the Linked Data page.

Food Frequency Questionnaire

Where the food frequency questionnaire has been used, Cancer Council Victoria must be acknowledged with the statement "The authors thank Professor Graham Giles and Professor Roger Milne of the Cancer Epidemiology Centre of Cancer Council Victoria, for permission to use the Dietary Questionnaire for Epidemiological Studies (Version 2), Melbourne: Cancer Council Victoria, 1996." Furthermore, all parties are to notify each other before presenting any DQES data at a conference, seminar or other forum, and, where appropriate, must provide copies of the presentation, papers etc. to the Director of the Cancer Epidemiology Centre.

Additional funding agencies should also be acknowledged if this is applicable. The acknowledgement may refer to any other persons who have provided comments, advice, support or other input into the paper, who are not already listed as authors. Permission should be sought from these persons before including their names.

 Plain language research summaries

Plain language summaries (or lay summaries) are short accounts of research that are written for members of the general public (and researchers from other fields of study). They explain research to the non-expert. Plain language summaries provide a bigger picture context for the research and show why it is important. They are useful in supporting wider public engagement with research and are particularly important for research in medicine and health.

Plain language summaries support the dissemination of research to patients, participants, other scientists, health professionals and policymakers. They are written so the intended audience can read, understand and act upon the first time they read it.

Below is a link to a plain language summary template. We encourage you to use this template and share your summary. Please email a copy of your summary to our Communications and Engagement Officer for inclusion on this website and in newsletters and social media. 

Download the Plain language summary template (Word Document)

Social Media


The study uses its Twitter profile (@ALSWH_Official) to disseminate outcomes to researchers and NGOs with an interest in women's health research, policy and practice. If you're publishing or presenting at a conference us please tag us in your tweets. 


The study's Facebook page presents research outcomes and health-related information to a lay audience. We would be happy to help promote suitably presented articles, videos, or infographics highlighting research results from our survey data. 

To discuss content please contact our Communications & Engagement Officer

Requests from journals for information about participant involvement

Before every pilot and every mail survey all of the participant comments from previous surveys are reviewed. The pilot surveys include an evaluation survey, as well as open ended responses which are taken into consideration when formulating the main survey. Thus participants have the opportunity to comment at every survey and in that sense are heavily involved in survey development. Additionally, the ALSWH provides participants with a free call 1800 telephone number, email and social media channels for interaction with the research team. All concerning comments made in surveys by participants are followed up with a personal phone call from the research team.

Requests from journals for information about data access

Use of the ALSWH dataset is subject to strict ethical conditions due to the personal nature of the data collected. The ethics committees that oversee the ALSWH are the Australian Government Department of Health Human Research Ethics Committee and the Human Research Ethics Committees at the University of Queensland and the University of Newcastle. Ethical approval of the ALSWH specifies that de-identified data are only available to collaborating researchers where there is a formal request to make use of the material, and that each request has to be approved by the ALSWH Data Access Committee. Further details can be found at

Consent in the 1989-95 cohort

In the initial online survey participants indicated their consent to participate in the ALSWH study by completing the survey, consenting to data linkage and providing their personal details, which were validated by the Australian Department of Human Services.

Participants have been informed at each survey that researchers will be comparing their information with that collected in earlier surveys. Completion of the survey was taken as consent. This method of consent was approved by the Australian Department of Health, the Australian Department of Human Services, and both the University of Queensland (UQ) and the University of Newcastle (UoN) Human Research Ethics Committees (HREC). At each wave, participants are offered the chance to win multiple prizes on completion of their survey. This was deemed necessary after consultations with women in the target age group in the planning phase of the study. Each prize draw has been approved by both UoN and UQ HRECs as appropriate compensation for participation. Participants have been and will be consistently informed that participation is voluntary and they are free to discontinue involvement at any time.

Data Books

A data book is produced using the data collected from each of the surveys. These books contain percentages of responses for each item asked in the surveys, by area of residence.

View and download the data books (in Mircosoft Excel) for all available surveys by cohort using the links below.

1989-95 Cohort
  Data Book for the 1989-95 Cohort
1973-78 Cohort   Data Book for the 1973-78 Cohort
1973-78 Cohort   Data Book of Child Data for the 1973-78 Cohort
1946-51 Cohort   Data Book for the 1946-51 Cohort
1921-26 Cohort   Data Book for the 1921-26 Cohort Surveys 1-6
1921-26 Cohort 6MF   Data Book for the 1921-26 Cohort Six Monthly Follow-Up

View and download the data books (PDF) for individual surveys by cohort using the links below.

2019   Data Book of Child Data for the 1989-95 Cohort
2018-2019   1973-78 cohort Survey 8
2017   1989-95 cohort Survey 5
2017   1921-26 cohort Six Monthly Follow up Surveys 11-12
2016   1946-51 cohort Survey 8
2016   1989-95 cohort Survey 4
2016   1921-26 cohort Six Monthly Follow up Surveys 9-10
2015   1989-95 cohort Survey 3
2015   1921-26 cohort Six Monthly Follow up Surveys 7-8
2015   1973-78 cohort Survey 7
2014   1921-26 cohort Six Monthly Follow up Surveys 5-6
2014   1989-95 cohort Survey 2
2013   1989-95 cohort Survey 1
2013   1946-51 cohort Survey 7 (62-67 years)
2013   1921-26 cohort Six Monthly Follow up Surveys 3-4
2012   1921-26 cohort Six Monthly Follow Up Surveys 1-2
2012   1973-78 cohort Survey 6 
(34-39 years)
2011   1921-26 cohort Survey 6
 (85-90 years)
2010   1946-51 cohort Survey 6
 (59-64 years)
2009   1973-78 cohort Survey 5
 (31-36 years)
2008   1921-26 cohort Survey 5 
(82-87 years)
2007   1946-51 cohort Survey 5
 (56-61 years)
2006   1973-78 cohort Survey 4
 (28-33 years)
2005   1921-26 cohort Survey 4 
(79-84 years)
2004   1946-51 cohort Survey 4 
(53-58 years)
2003   1973-78 cohort Survey 3 
(25-30 years)
2002   1921-26 cohort Survey 3 
(76-81 years)
2001   1946-51 cohort Survey 3 
(50-55 years)
2000   1973-78 cohort Survey 2 
(22-27 years)
1999   1921-26 cohort Survey 2 
(73-78 years)
1998   1946-51 cohort Survey 2 
(47-52 years)
1996   1973-78 cohort Survey 1 
(18-23 years)
1996   1921-26 cohort Survey 1 
(70-75 years)
1996   1946-51 cohort Survey 1
 (45-50 years)